Domenico_Asimomitis_ICML_2023

Code accompanying "High-Resolution Interpretable Classification of Artifacts versus Real Variants in Whole Genome Sequencing Data from Archived Tissue" by Domenico & Asimomitis et al. https://icml-compbio.github.io/2023/papers/WCBICML2023_paper116.pdf

📁 Content

The repository contains the following directories:

└─ notebooks/: folder containing the jupyter notebooks with code to:
   └─ build/train the model (Model.ipynb)
   └─ generate the output and interpretability maps (Output.ipynb)
└─ data/: folder containing two test cases
└─ output/: folder containing the output of the notebooks for the two test cases of the data folder
└─ model/: folder containing the trained pytorch model

▶️ Getting Started

Clone the repository

To clone this repository on your local computer please run:

$ git clone https://github.com/papaemmelab/Domenico_Asimomitis_ICML_2023

Run notebooks

To run the notebooks please first install jupyter here. For the python environment necessary to be installed please use:

pip install -r requirements.txt

📧 Contact

For any questions, please contact Dylan or Georgios.